Urban green per capita — green_capita • ediblecity

This indicators calculates the amount of green per capita in the city. This may include private green such as gardens and crops or exclude them.

Usage

green_capita(
  x,
  green_categories = NULL,
  inhabitants = NULL,
  neighbourhoods = NULL,
  inh_col = NULL,
  name_col = NULL,
  private = FALSE,
  verbose = FALSE,
  min_inh = 0
)

Arguments

x: An 'sf' object with the urban model of your city and a 'land_use' column with categories of urban features.
green_categories: The categories that are considered as urban green. If NULL, categories of 'city_land_uses' are considered.
inhabitants: A value representing the inhabitants in the city.
neighbourhoods: (optional) An 'sf' object with polygons representing the neighborhoods in the city.
inh_col: (optional) The col in 'x' or in 'neighborhoods' indicating the inhabitants in each neighborhood.
name_col: (optional) The col in 'x' or in 'neighborhoods' indicating the name of each neighborhood
private: If FALSE (default), only public areas are considered in the indicator. If TRUE, elements in 'city_land_uses' where 'private' is TRUE are considered. Alternatively, a vector with land_uses to be considered.#'
verbose: If FALSE (default), the indicator returns the proportion between the most and the least green neighbourhoods. Otherwise, it will return a tibble with the green per capita in each neighborhood, provided that 'inh_col' and 'name_col' are provided.
min_inh: If neighbourhoods are used, those with less inhabitants than 'min-inh' will be discarded.

Value

A numeric value expressing the square meters of green per capita. Or a numeric value expressing the proportion between the greenest and the least green neighbourhood. Or a tibble with the green area, inhabitants and green per capita in each neighbourhood.

Details

If 'inh_col' and 'name_col' are defined and 'neighbourhoods' is NULL, the function searches the columns in 'x'. If 'neighbourhoods' is defined along with previous both, the columns are searched in 'neighbourhoods' and spatially joined with 'x'. In both cases, 'inhabitants' is ignored.

Author

Josep Pueyo-Ros

Examples

# Calculate total green per capita in the city
green_capita(city_example, inhabitants = 6000)
#> [1] 5.113167

# Calculate the differences between the greenest and the least green neighbourhoods
green_capita(city_example, neighbourhoods = neighbourhoods_example,
             inh_col = "inhabitants", name_col = "name")
#> [1] 0.1528437

# Get the green per capita in each neighbourhood
green_capita(city_example, neighbourhoods = neighbourhoods_example,
             inh_col = "inhabitants", name_col = "name", verbose = TRUE)
#> # A tibble: 2 × 4
#>   name              area inhabitants green_capita
#>   <chr>            <dbl>       <dbl>        <dbl>
#> 1 Sant Narcís nord 20016        1028        19.5 
#> 2 Sant Narcís sud  15743        5290         2.98

# Use a customized vector of land_uses to be considered private green
green_capita(city_example, inhabitants = 6000, private = c("Normal garden", "Commercial garden"))
#> [1] 10.67717